In this work an improvement of an initial approach to design Artificial Neural Networks to forecast Time Series is tackled, and the automatic process to design Artificial Neural N...
We propose PASTE, the first differentially private aggregation algorithms for distributed time-series data that offer good practical utility without any trusted server. PASTE add...
We propose the development of a prediction market to provide a form of collective intelligence for forecasting prices for "toxic assets" to be transferred from Irish bank...
Volunteer-based grid computing resources are characteristically volatile and frequently become unavailable due to the autonomy that owners maintain over them. This resource volati...
In this paper, we propose an approach to flow-unaware admission control, which is combination with an aggregate packet forwarding scheme, improves scalability of networks while g...